Survivorship bias

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Survivorship bias

Usually pertaining to fund manager or individual investor performance. Suppose we examined the performance over the last ten years of a group of managers that exist today. This performance is biased upwards because we are only considering those that survived for 10 years. That is, some dropped out because of poor performance. Hence, in evaluating performance, one has to be careful to include both the current and the managers that dropped out of the sample due to poor performance.

Survivorship Bias

In finance, the tendency to exclude failed companies or managers from performance evaluations or studies simply because they do not exist. Survivorship bias can result in skewed findings in a study and lead a casual reader to believe that a study shows a rosier picture than it really does. Mutual funds, especially smaller ones, are especially susceptible to survivorship bias. At any given time, 90% of mutual funds will claim to be in the top 25% of performers. Technically, they are correct, but only because the other 75% have closed or merged. Manager universe comparisons have also been criticized for exhibiting signs of survivorship bias. It is also known as survivor bias.

Although this second explanation is responsible for only a small amount of the large increase in ROA (as we shall see, very few de novo banks fail after only two years of operation), it is a good illustration of how survivor bias can affect our results.

The Z-score analysis discussed above provides some support for these hypothetical hazard functions, but that evidence is crude at best and suffers from survivor bias in the data.

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